From carbon stocks to Maya ruins, data sharing fosters discovery
Woodwell Climate data aids archaeologists in uncovering ancient city in the Mexican jungle
Forests of Mexico’s Yucatán Peninsula, which was densely settled by the Ancient Maya Civilization.
Image courtesy of Phil/Flickr
Under the thick forest of Mexico’s Yucatán Peninsula, the ancient ruins of a Maya City have been uncovered with the use of remote sensing.
Of course, that wasn’t the outcome that Woodwell Climate’s Chief Scientific Officer, Dr. Wayne Walker, anticipated when he and his team collected and processed the remote sensing dataset for an unrelated project nearly a decade ago.
Walker’s team was mapping the region as part of the Mexico REDD+ project, a collaborative, international effort to explore strategies for reducing emissions from deforestation and degradation in the country. Using a remote sensing technology called LiDAR, which scans terrain from a low-flying plane using pulses of laser light, Walker and project collaborators created a comprehensive map of forests—and the carbon they contain—across Mexico.
Walker and team coordinated the flights and processed the raw data for use in the project, uploading it afterwards to a website for public use. But, once the project ended, he all but forgot about the effort, apart from responding occasionally to researchers interested in downloading the dataset for their own work.
One of those researchers was Luke Auld-Thomas, a PhD candidate at Tulane University researching the Classic Maya civilization, which thrived in the Yucatan until the 9th century when much of the region was abandoned, though their culture and languages persist to this day. Because of its unique ability to provide a detailed three-dimensional picture of whatever features are present on the ground, LiDAR imagery is an incredibly powerful tool for a multitude of purposes, from climate science to archaeology. And while the Mexico REDD+ project was interested in documenting the forests, Auld-Thomas was interested in what might be hidden beneath them.
LiDAR imagery of the Amazon Rainforest.
image by Manoela Machado
“One scientist’s noise is another’s entire field of study,” says Walker. “In our other projects, like Climate Smart Martha’s Vineyard, we see historical structures like stone walls that aren’t necessarily meaningful to our work but could be of interest to archaeologists.”
In Mexico, the large areas surveyed by Woodwell Climate revealed not just individual human-built structures, but the plazas, reservoirs, and ball courts of an entire, previously undocumented city. The discovery, published in the journal Antiquity, supported the theory that the region was, in fact, densely settled during the height of Classic Maya civilization.
“We knew that it was close to a lot of interesting sites and settlements— areas of large-scale landscape modification that had been mapped and studied— but none of the survey areas themselves were actually places that archeologists ever worked, making it a really exciting sample to work with,” said Auld-Thomas.
map by Christina Shintani
Auld-Thomas had specifically been on the hunt for a pre-existing LiDAR dataset like the one Walker helped create— a survey conducted for completely non-archaeological purposes and therefore free of any biases. Essentially a “random sample” of the region. That randomness, and the subsequent discovery of an entire city, allowed Auld-Thomas and his colleagues to more strongly argue their point about intense urbanization in the Yucatán.
“If you’re only going to places where you know there’s going to be something, then of course, you’re going to find something significant, right? These random samples, not collected for archeological purposes, are gold in some respects,” said Dr. Marcello Canuto, who co-authored the paper. Canuto directs the Middle American Research Institute at Tulane, where the research for this study was conducted.
The unexpected outcome of the LiDAR survey offers a textbook example of the value of open data access. Sharing data and resources both within and between fields of science can jumpstart discovery and distribute the costs of an otherwise expensive data collection effort.
“Just look at what came out of the moonshot,” says Canuto. Thousands of technologies, developed in humanity’s pursuit of the moon landing, have found unforeseen applications in today’s world— including LiDAR.
“Certainly, many of us have produced datasets that have led to incremental advances in closely related fields,” says Walker. “But here is a special case of open source data advancing discovery in an entirely unrelated field of study.”
Advancements across fields continue to better our understanding of the world around us. And the lessons learned from a civilization like the Maya have very real parallels to today’s climate crisis.
As Auld-Thomas and Canuto show, the Maya densely settled the Yucatán Peninsula, maxing out the capacity of the surrounding environment to support their population. And then the regional climate shifted. A long-term drought settled in, resources became scarcer, governments became unstable, people started leaving the cities, and the infrastructure of the larger civilization collapsed.
“The reason environmental scientists collect LiDAR data of the forest, is that they are trying to understand environmental processes in order to help human societies conserve the landscape,” says Auld-Thomas. “As archaeologists, we try to understand how people in these exact environmental contexts have confronted deforestation and climate change and all of these other things before.”
For Canuto, the lesson to be learned lies not just in the environmental perils, but in the societal ones. Because what complex societies hate— be they the Classic Maya or today’s modern culture— is a lack of predictability. If a system cannot adapt, it will fail.
“The collapse was more than just climate change,” says Canuto. “It was a failure of a political system to respond to climate change.”
